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My photo Finally, I am establishing a new presence on the web. If you arrived here via my old page at UIUC, good. If you arrived here via a search engine, even better, and if you found your way here through a link from some other source, I am surprised. Thanks for stopping by.

Unlike the page at UIUC, I plan to maintain the information here. The CV and résumé, for example, are reasonably up-to-date.

The near-term goals with this site are to get my old content here and updated as necessary and figure out what to do with the geneagrapher. Also, I am considering writing a simple system for managing my pages. We'll see.

About Me

Academic Background

Parallel graph coloring In May 2007, I completed my Ph.D. in Computer Science at the University of Illinois at Urbana-Champaign (UIUC). I specialized in scientific computing and am particularly interested in algorithm and data structure design and development. My dissertation studied parallel coarse grid selection algorithms for algebraic multigrid (AMG) under the guidance of my advisors Luke Olson and Paul Saylor.

I earned a M.S. in Computer Science at UIUC in 2004 under the guidance of Paul Saylor. My Masters research was influenced heavily by the work I did in my first summer at the Center for Applied Scientific Computing at Lawrence Livermore National Laboratory.

Further back, I earned a B.S. in Biological Science and Computer Science at the University of Iowa.

Publications

Current Status

Shortly after completing my Ph.D., I started a postdoctoral position in the Scientific Computing Center (now the Materials and Computational Science Center) at the National Renewable Energy Laboratory (NREL) in Golden, Colorado.

My primary project at NREL is part of a computational systems biology project called "Green Energy: Advancing Bio-hydrogen". Briefly, the project aims to: (1) construct a comprehensive metabolic model for the hydrogen-producing green alga Chlamydomonas reinhardtii; (2) produce high-performance software for solving problems arising from the rate equations encoded in the model.